Automation and intelligence are the formula for AI success in the money management realm.
Artificial intelligence is up and running in the U.S. financial services sector, with the latest Nvidia State of AI in Financial Services Report noting how far and how fast the technology has come in only a few years.
In the survey of 400 corporate finance executives, Nvidia found that 91% of finance firms either “assessing or using AI” to improve operational efficiency, identify new opportunities, and enhance customer experiences.
“Portfolio optimization, fraud detection, and risk management remain top AI use cases, while generative AI is popular with organizations keen to drive efficiencies,” the survey noted. AI backers have clarified that finance is a tailor-made industry for AI, where data is king, and technology has historically boosted the industry’s fortunes over the last century.
Dan Durn, chief financial officer at digital document and imaging giant Adobe, is the latest to champion AI for the corporate finance world.
In a new interview out this week in Forbes, Durn said AI has the potential to take the corporate finance realm to new heights in ways that will “dramatically reshape” the sector.
“As you think about rules-based work, you have an opportunity not only to automate but to inject intelligence into the process,” Durn told Forbes. “This frees up bandwidth, as people can focus on upskilling their capabilities and focus on more strategic work.”
Durn cites the “velocity” of AI insights gathered and pushed at the edge of the organization “to help feed the business and sharpen business decision-making and then democratize access to data that’s at the core of this inflection.”
Best Use Cases in “Opportunity Spaces”
At Adobe, Durn said a recent company “hackathon” mission revealed several key areas where AI works best for finance departments, tabbing them as “opportunity spaces.”
“(For example), There’s a lot of unstructured data out there,” Durn told Forbes. “PDF is the most common file format on the planet. Getting structured data extracted from that unstructured file format is a huge opportunity in the insights that you can get. So unstructured to structured data.”
Durn also cited an opportunity in predictive forecasting, where artificial intelligence can gather data, evaluate it, and use it to build a “predictive forecasting engine that accurately reflects the performance of the business that runs alongside the normal planning cycle and get insights quickly.
Another “best use” scenario for AI in finance is with chatbots, mainly when used internally.
“When you think about our employment manuals, if you think about compensation and how we operate, if you think about our equity program, there’s a lot of policies and procedures in place that define how a company operates,” he said. “When you can ring-fence that data and use a chatbot as your first line of engagement with employees to surface the standard questions you get, employees efficiently get the answers that they’re looking for, and the capabilities we put in place as a company can then be used to go deep with the complex set of questions that employees have.”
Above all, AI in finance is all about solving problems, Durn added.
“Keep the business focus,” he said. “What business problem are we solving? Keep that at the forefront. That’s how you get business leaders excited about supporting [and] adopting these technologies.”
Brian O’Connell, a former Wall Street bond trader and best-selling author, is a prominent figure in the finance industry. With a substantial background as an ex-Wall Street trader, he has authored two best-selling books: ‘The 401k Millionaire’ and ‘CNBC’s Creating Wealth’, demonstrating his profound knowledge of finance and investing.
Brian is also a finance and business writer for esteemed national platforms and publications, including CNN, TheStreet.com, CBS News, The Wall Street Journal, U.S. News & World Report, Forbes, and Fox News.
